This invention relates to a self-learning method and apparatus for dynamic system characterisation and simulation.
In general, mathematical modelling or simulation of dynamic systems in which there are significant lags between changes in input variable and consequent changes in an output variable is computationally intensive. Various self-learning adaptive processes have been proposed, but these tend to require very considerable data storage and very long learning periods are required. Furthermore, such systems cannot cope well with situations in which there are significant lags.
The applicant has established that, where the changes in the input variables are cyclic, a relatively simple technique for modelling the dynamic system can be used to give accurate predictions of the system behaviour.